Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

Background: Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care. Methods: Our analyses included 14 886 meta-analyses from the Cochrane Database of Systematic Reviews. We classified each meta-analysis according to the type of outcome, type of intervention comparison and medical specialty. By modelling the study data from all meta-analyses simultaneously, using the log odds ratio scale, we investigated the impact of meta-analysis characteristics on the underlying between-study heterogeneity variance. Predictive distributions were obtained for the heterogeneity expected in future meta-analyses. Results Between-study heterogeneity variances for meta-analyses in which the outcome was all-cause mortality were found to be on average 17% (95% CI 10–26) of variances for other outcomes. In meta-analyses comparing two active pharmacological interventions, heterogeneity was on average 75% (95% CI 58–95) of variances for non-pharmacological interventions. Meta-analysis size was found to have only a small effect on heterogeneity. Predictive distributions are presented for nine different settings, defined by type of outcome and type of intervention comparison. For example, for a planned meta-analysis comparing a pharmacological intervention against placebo or control with a subjectively measured outcome, the predictive distribution for heterogeneity is a log-normal (−2.13, 1.582) distribution, which has a median value of 0.12. In an example of meta-analysis of six studies, incorporating external evidence led to a smaller heterogeneity estimate and a narrower confidence interval for the combined intervention effect. Conclusions: Meta-analysis characteristics were strongly associated with the degree of between-study heterogeneity, and predictive distributions for heterogeneity differed substantially across settings. The informative priors provided will be very beneficial in future meta-analyses including few studies

Intergenerational change and familial aggregation of body mass index

The relationship between parental BMI and that of their adult offspring, when increased adiposity can become a clinical issue, is unknown. We investigated the intergenerational change in body mass index (BMI) distribution, and examined the sex-specific relationship between parental and adult offspring BMI. Intergenerational change in the distribution of adjusted BMI in 1,443 complete families (both parents and at least one offspring) with 2,286 offspring (1,263 daughters and 1,023 sons) from the west of Scotland, UK, was investigated using quantile regression. Familial correlations were estimated from linear mixed effects regression models. The distribution of BMI showed little intergenerational change in the normal range (\25 kg/m2), decreasing overweightness (25– \30 kg/m2) and increasing obesity (C30 kg/m2). Median BMI was static across generations in males and decreased in females by 0.4 (95% CI: 0.0, 0.7) kg/m2; the 95th percentileincreased by 2.2 (1.1, 3.2) kg/m2 in males and 2.7 (1.4, 3.9) kg/m2 in females. Mothers’ BMI was more strongly associated with daughters’ BMI than was fathers’ (correlation coefficient (95% CI): mothers 0.31 (0.27, 0.36), fathers 0.19 (0.14, 0.25); P = 0.001). Mothers’ and fathers’ BMI were equally correlated with sons’ BMI (correlation coefficient: mothers 0.28 (0.22, 0.33), fathers 0.27 (0.22, 0.33). The increase in BMI between generations was concentrated at the upper end of the distribution. This, alongside the strong parent-offspring correlation, suggests that the increase in BMI is disproportionally greater among offspring of heavier parents. Familial influences on BMI among middle-aged women appear significantly stronger from mothers than father

Can we apply the Mendelian randomization methodology without considering epigenetic effects?

<p>Abstract</p> <p>Introduction</p> <p>Instrumental variable (IV) methods have been used in econometrics for several decades now, but have only recently been introduced into the epidemiologic research frameworks. Similarly, Mendelian randomization studies, which use the IV methodology for analysis and inference in epidemiology, were introduced into the epidemiologist's toolbox only in the last decade.</p> <p>Analysis</p> <p>Mendelian randomization studies using instrumental variables (IVs) have the potential to avoid some of the limitations of observational epidemiology (confounding, reverse causality, regression dilution bias) for making causal inferences. Certain limitations of randomized controlled trials, such as problems with generalizability, feasibility and ethics for some exposures, and high costs, also make the use of Mendelian randomization in observational studies attractive. Unlike conventional randomized controlled trials (RCTs), Mendelian randomization studies can be conducted in a representative sample without imposing any exclusion criteria or requiring volunteers to be amenable to random treatment allocation.</p> <p>Within the last decade, epigenetics has gained recognition as an independent field of study, and appears to be the new direction for future research into the genetics of complex diseases. Although previous articles have addressed some of the limitations of Mendelian randomization (such as the lack of suitable genetic variants, unreliable associations, population stratification, linkage disequilibrium (LD), pleiotropy, developmental canalization, the need for large sample sizes and some potential problems with binary outcomes), none has directly characterized the impact of epigenetics on Mendelian randomization. The possibility of epigenetic effects (non-Mendelian, heritable changes in gene expression not accompanied by alterations in DNA sequence) could alter the core instrumental variable assumptions of Mendelian randomization.</p> <p>This paper applies conceptual considerations, algebraic derivations and data simulations to question the appropriateness of Mendelian randomization methods when epigenetic modifications are present.</p> <p>Conclusion</p> <p>Given an inheritance of gene expression from parents, Mendelian randomization studies not only need to assume a random distribution of alleles in the offspring, but also a random distribution of epigenetic changes (e.g. gene expression) at conception, in order for the core assumptions of the Mendelian randomization methodology to remain valid. As an increasing number of epidemiologists employ Mendelian randomization methods in their research, caution is therefore needed in drawing conclusions from these studies if these assumptions are not met.</p

The burden of neglected tropical diseases in Ethiopia, and opportunities for integrated control and elimination

Background: Neglected tropical diseases (NTDs) are a group of chronic parasitic diseases and related conditions that are the most common diseases among the 2·7 billion people globally living on less than US$2 per day. In response to the growing challenge of NTDs, Ethiopia is preparing to launch a NTD Master Plan. The purpose of this review is to underscore the burden of NTDs in Ethiopia, highlight the state of current interventions, and suggest ways forward. Results: This review indicates that NTDs are significant public health problems in Ethiopia. From the analysis reported here, Ethiopia stands out for having the largest number of NTD cases following Nigeria and the Democratic Republic of Congo. Ethiopia is estimated to have the highest burden of trachoma, podoconiosis and cutaneous leishmaniasis in sub-Saharan Africa (SSA), the second highest burden in terms of ascariasis, leprosy and visceral leishmaniasis, and the third highest burden of hookworm. Infections such as schistosomiasis, trichuriasis, lymphatic filariasis and rabies are also common. A third of Ethiopians are infected with ascariasis, one quarter is infected with trichuriasis and one in eight Ethiopians lives with hookworm or is infected with trachoma. However, despite these high burdens of infection, the control of most NTDs in Ethiopia is in its infancy. In terms of NTD control achievements, Ethiopia reached the leprosy elimination target of 1 case/10,000 population in 1999. No cases of human African trypanosomiasis have been reported since 1984. Guinea worm eradication is in its final phase. The Onchocerciasis Control Program has been making steady progress since 2001. A national blindness survey was conducted in 2006 and the trachoma program has kicked off in some regions. Lymphatic Filariasis, podoconiosis and rabies mapping are underway. Conclusion: Ethiopia bears a significant burden of NTDs compared to other SSA countries. To achieve success in integrated control of NTDs, integrated mapping, rapid scale up of interventions and operational research into co implementation of intervention packages will be crucial

Oxaliplatin induces drug resistance more rapidly than cisplatin in H69 small cell lung cancer cells

Cisplatin produces good responses in solid tumours including small cell lung cancer (SCLC) but this is limited by the development of resistance. Oxaliplatin is reported to show activity against some cisplatin-resistant cancers but there is little known about oxaliplatin in SCLC and there are no reports of oxaliplatin resistant SCLC cell lines. Studies of drug resistance mainly focus on the cellular resistance mechanisms rather than how the cells develop resistance. This study examines the development of cisplatin and oxaliplatin resistance in H69 human SCLC cells in response to repeated treatment with clinically relevant doses of cisplatin or oxaliplatin for either 4 days or 2h. Treatments with 200ng/ml cisplatin or 400ng/ml oxaliplatin for 4 days produced sublines (H69CIS200 and H69OX400 respectively) that showed low level (approximately 2-fold) resistance after 8 treatments. Treatments with 1000ng/ml cisplatin or 2000ng/ml oxaliplatin for 2h also produced sublines, however these were not stably resistant suggesting shorter treatment pulses of drug may be more effective. Cells survived the first five treatments without any increase in resistance, by arresting their growth for a period and then regrowing. The period of growth arrest was reduced after the sixth treatment and the H69CIS200 and H69OX400 sublines showed a reduced growth arrest in response to cisplatin and oxaliplatin treatment suggesting that "regrowth resistance" initially protected against drug treatment and this was further upregulated and became part of the resistance phenotype of these sublines. Oxaliplatin dose escalation produced more surviving sublines than cisplatin dose escalation but neither set of sublines were associated with increased resistance as determined by 5-day cytotoxicity assays, also suggesting the involvement of regrowth resistance. The resistant sublines showed no change in platinum accumulation or glutathione levels even though the H69OX400 subline was more sensitive to buthionine sulfoximine treatment. The H69CIS200 cells were cross-resistant to oxaliplatin demonstrating that oxaliplatin does not have activity against low level cisplatin resistance. Relative to the H69 cells, the H69CIS200 and H69OX400 sublines were more sensitive to paclitaxel and taxotere suggests the taxanes may be useful in the treatment of platinum resistant SCLC. These novel cellular models of cisplatin and oxaliplatin resistant SCLC will be useful in developing strategies to treat platinum-resistant SCLC

ERCC1 expression and RAD51B activity correlate with cell cycle response to platinum drug treatment not DNA repair

Background: The H69CIS200 and H69OX400 cell lines are novel models of low-level platinum-drug resistance. Resistance was not associated with increased cellular glutathione or decreased accumulation of platinum, rather the resistant cell lines have a cell cycle alteration allowing them to rapidly proliferate post drug treatment. Results: A decrease in ERCC1 protein expression and an increase in RAD51B foci activity was observed in association with the platinum induced cell cycle arrest but these changes did not correlate with resistance or altered DNA repair capacity. The H69 cells and resistant cell lines have a p53 mutation and consequently decrease expression of p21 in response to platinum drug treatment, promoting progression of the cell cycle instead of increasing p21 to maintain the arrest. Conclusion: Decreased ERCC1 protein and increased RAD51B foci may in part be mediating the maintenance of the cell cycle arrest in the sensitive cells. Resistance in the H69CIS200 and H69OX400 cells may therefore involve the regulation of ERCC1 and RAD51B independent of their roles in DNA repair. The novel mechanism of platinum resistance in the H69CIS200 and H69OX400 cells demonstrates the multifactorial nature of platinum resistance which can occur independently of alterations in DNA repair capacity and changes in ERCC1

The American Experience With Desmopressin

Conclusive evidence of a polyuric etiology from a failure of vasopressin elevation led to a new pharmacologic approach to the treatment of childhood nocturnal enuresis. Desmopressin acetate, a vasopressin analogue, has been used successfully since 1978 to treat this condition. Desmopressin's efficacy at doses of 5 to 40 μg has been demonstrated in Europe and the United States. Similarly, its safety has been established, and it is a first-line choice for physicians worldwide.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67214/2/10.1177_000992289303200107.pd

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

An empirical study using permutation-based resampling in meta-regression

<p>Abstract</p> <p>Background</p> <p>In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate <it>P </it>values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression.</p> <p>Methods</p> <p>We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final <it>P </it>values between methods.</p> <p>Results</p> <p>We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The <it>P </it>values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases.</p> <p>Conclusions</p> <p>We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase <it>P </it>values in meta-regression of multiple covariates for relatively small amount of trials.</p